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Neal lesh-1202742298252135-3 (5)

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  • I’m going to start with what somehow seems like a fun example, which is that if you bought a more expensive ticket on the titanic, not only do you get nicer food, but you’ve got a higher chance of surviving the trip, as shown in this graph. these numbers are real, though it would be a little more fair to show men, women, and children separately ... since this is one of the few cases of where being a woman or child is protective. but moving onto some statistics which I think is the most disturbing of the talk...
  • Okay, so on to the world. And one thing about this talk and public health in general, in that it’s pretty focused on people and their basic needs. not so much the animals. not even so much the environment, though that’s certainly important for our health. but we can start with how many of us there are. and there’s about 6.1 billion people, and counting... and population growth is certainly a factor for public health
  • Okay, so on to the world. And one thing about this talk and public health in general, in that it’s pretty focused on people and their basic needs. not so much the animals. not even so much the environment, though that’s certainly important for our health. but we can start with how many of us there are. and there’s about 6.1 billion people, and counting... and population growth is certainly a factor for public health
  • Okay, so on to the world. And one thing about this talk and public health in general, in that it’s pretty focused on people and their basic needs. not so much the animals. not even so much the environment, though that’s certainly important for our health. but we can start with how many of us there are. and there’s about 6.1 billion people, and counting... and population growth is certainly a factor for public health
  • Okay, so on to the world. And one thing about this talk and public health in general, in that it’s pretty focused on people and their basic needs. not so much the animals. not even so much the environment, though that’s certainly important for our health. but we can start with how many of us there are. and there’s about 6.1 billion people, and counting... and population growth is certainly a factor for public health
  • Okay, so on to the world. And one thing about this talk and public health in general, in that it’s pretty focused on people and their basic needs. not so much the animals. not even so much the environment, though that’s certainly important for our health. but we can start with how many of us there are. and there’s about 6.1 billion people, and counting... and population growth is certainly a factor for public health
  • Paying volunteers, discussing work-for-food programs over fancy dinner during famine,
  • In Tanzania: under-5 mortality was 13% lower in the two IMCI districts compared to non-IMCI districts and there was a s ignificant impact on stunting

Transcript

  • 1. Computer science applications to improve health delivery in low-income countries. Neal Lesh
  • 2.  
  • 3. My Story
    • Mid-thirties computer researcher seeks more fulfilling career. Goes back to school then off to Africa. Discovers things are more simple and more complex than he originally imagined. Can't imagine doing anything else...
  • 4. Outline
    • Background
      • The simplicity and complexity of global inequity
    • Two examples
      • Patient record systems for AIDS treatment
      • Medical algorithms on handhelds
    • Conclusion
  • 5. Risk Factor
    • for surviving the Titanic.
    % survived Poverty as a
  • 6. Global Health
  • 7. Simple Story $$$$$$$$$$$$$$$$ $$$$$$$$$$$$$$$$ $$$$$$$$$$$$$$$$ $$$$$$$$$$$$$$$$ $$$$$$$$$$$$$$$$ $$$$$$$$$$$$$$$$ $ Infant mortality: 5 per 1,000 births Maternal mortality: 8 per 100K births Life expectancy: 78 years Infant mortality: 95 per 1,000 births Maternal mortality: 500-1000 per 100K Life expectancy: 45 years 300-540 57 69
  • 8. Simple Story $$$$$$$$$$$$$$$$ $$$$$$$$$$$$$$$$ $$$$$$$$$$$$$$$$ $$$$$$$$$$$$$$$$ $$$$$$$$$$$$$$$$ $$$$$$$$$$$$$$$$ $
  • 9. Simple Story $$$$$$$$$$$$$$$$ $$$$$$$$$$$$$$$$ $$$$$$$$$$$$$$$$ $$$$$$$$$$$$$$$$ $$$$$$$$$$$$$$$$ $$$$$$$$$$$$$ $$$$ Infant mortality: 95 per 1,000 births Maternal mortality: 500-1000 per 100,000 b Life expectancy: 45 years
  • 10. Simple Story “ We are the first generation that can end poverty. ” - Eveline Herfkens, UN Millennium Campaign
  • 11. Complexity
    • Corruption, careerism, tax write-offs
    • 5-star poverty alleviation meetings
    • Unintended consequences, e.g., paying volunteers
    • Imperialism & foreign experts
    • “ If you want to build a ship, don't drum up people to collect wood and don't assign them tasks and work, but rather teach them to long for the endless immensity of the sea.”
      • Antoine de Saint-Exupery
  • 12. Information as Care
    • Study: rigorous application of standard treatment protocols reduced in-hospital mortality in children’s malaria cases by 50%
    • Clinician’s complaint: where are my lab results?!
    • Patient Knowledge Example: five danger signs for seeking care during and after labor.
  • 13. Outline
    • Background
      • The simplicity and complexity of global inequity
    • Two examples
      • Patient record systems for AIDS treatment
      • Medical algorithms on handhelds
    • Conclusion
  • 14.
    • One year later
    AIDS Treatment in Rural Rwanda
  • 15.
    • One year later
    Improving Health Systems
  • 16.
    • One year later
    Connecting to the Internet
  • 17. Electronic Medical Record (EMR) Patient Monitoring Reports Clinicians & Patients Managers EMR Staff Paper forms Program Monitoring Reports Funder & government reports $ Re-allocate resources
  • 18. Patient Monitoring
  • 19. Missed-Visit List
  • 20. ICT task: satisfy reporting requests
  • 21. OpenMRS
    • Open source framework for medical record systems
    • www.openmrs.org
  • 22. Data Quality
    • Mistyped IDs
    • Missing & conflicting data
    • Backlog
    Potential solution: point-of-care systems
  • 23. Challenges & Opportunities
    • Keep up with demand
    • Increased impact on decision making
      • Inform to Improve (I2I) teams
    • Integration of lab and pharmacy components
    • Detecting important trends in data
  • 24. Outline
    • Background
      • The simplicity and complexity of global inequity
    • Two examples
      • Patient record systems for AIDS treatment
      • Medical algorithms on handhelds
    • Conclusion
  • 25. Rural Dispensary in Tanzania
  • 26. Standardized Care (IMCI)
  • 27. Standardized Care (IMCI)
  • 28. Standardized Care (IMCI)
  • 29. Tanzania: underfive mortality was 13% lower in the two IMCI districts Source: Schellenberg J et al Full IMCI in HF End of study 13% difference 95% CI: -7%, 30% Significant impact on stunting
  • 30. Deploying IMCI
    • IMCI
      • Shown to reduce mortality and morbidity
      • Adopted by ~100 countries
    • But uptake not as good as hoped
      • Training expensive
      • Correct use tapers off over time
      • Supervision challenging
  • 31. Why Automate IMCI?
  • 32. Why Automate IMCI?
    • Improve adherence
    • Improve supervision
    • Easier to update
    • More sophisticated protocols
    • Reduced training
  • 33. Field Work Results to be published in CHI’08
  • 34. How Automate IMCI?
  • 35. Exploratory Study
    • Pretesting & rapid iteration
    • Structured interviews
    • Observed trials w/ additional clinician to:
      • Ensure safety
      • Record adherence to IMCI
      • Record time
  • 36. Viral Training
  • 37. Key Findings
    • Must be
      • Fast
      • Flexible
      • Improve adherence to IMCI
    • Must address intentional deviation from IMCI
      • Temperature, respiratory rate
      • Advice
  • 38. Adherence Results Investigation Current practice adherence e-IMCI adherence p-value Vomiting 66.7% (n=24) 85.7% (n=28) - Chest indrawing 75% (n=20) 94.4% (n=18) - Blood in stool 71.4% (n=7) 100% (n=3) - Measles in the last 3 months 55.6% (n=9) 95.2% (n=21) < 0.05 Tender ear 0% (n=1) 100% (n=5) - All 61% (n=299) 84.7% (n=359) < 0.01
  • 39. Triaging patients on treatment for AIDS (Study ongoing in South Africa)
  • 40. e-CTC for HIV screening Counselors ask a series of questions leading to a patient assessment.
  • 41. CommCare Start House Hold Visit Plan Day Explore Data Exit
  • 42. House Hold Visit (Task Queue) 0 0 0:04:56 Register Birth Investigate Diarrhea of Sick Child Review malaria bed nets Topic of month: nutrition during pregnancy END VISIT
  • 43. Day Planning MKWERA : TB Referral (2 wks) MKEA: Severe diarrhea (3 days) CHUMA: late HH visit (3 months) KAIGILE: routine HH visit MGANDA: routine HH visit EXIT
  • 44. Outline
    • Background
      • The simplicity and complexity of global inequity
    • Two examples
      • Patient record systems for AIDS treatment
      • Medical algorithms on handhelds
    • Conclusion
  • 45. Conclusion
    • Key points
      • Must understand context
      • Much potential, many challenges
      • Keep it simple
    • Challenges
      • Evaluation, local ownership, I2I, duplication of effort, …
  • 46.
    • Thank you!
    • [email_address]